Abstract

Insurance solvency capital represents the financial resources required by an insurance company to absorb unexpected losses and remain capable of meeting its obligations to policyholders. Accurate estimation of solvency capital is essential because inadequate capital may expose insurers to financial distress, while excessive capital may reduce the efficient use of available financial resources. Actuarial risk models provide quantitative techniques for evaluating uncertainty associated with insurance claims, liabilities, and other sources of financial risk, making them useful tools for estimating appropriate solvency capital levels. The study examines the estimation of insurance solvency capital using actuarial risk models. It focuses on how actuarial modelling techniques can be applied to determine the level of capital required to protect insurers against unexpected losses and adverse changes in their risk exposure. The study will assess the usefulness of actuarial risk models in estimating capital requirements that reflect the underlying claims and financial risks faced by insurance companies. The study will consider actuarial measures such as claims frequency, claims severity, aggregate claims distributions, loss ratios, insurance liabilities, and risk exposure. Solvency capital will be assessed using measures such as required capital, available capital, solvency margins, capital adequacy ratios, and capital buffers. Actuarial techniques including probability distributions, stochastic modelling, simulation methods, risk measures, and stress testing will be considered in estimating potential loss outcomes and determining appropriate solvency capital requirements. A quantitative research approach will be adopted for the study. Relevant claims, financial, and underwriting data will be obtained from selected insurance companies and appropriate industry sources over a defined period. Descriptive statistics will be used to examine the characteristics of claims and financial risks, while actuarial risk models and statistical techniques will be applied to estimate aggregate losses and solvency capital requirements. Sensitivity analysis and stress testing may also be conducted to evaluate how changes in claims frequency, claims severity, investment risk, and other assumptions affect estimated capital requirements. The study is expected to show that actuarial risk models can provide reliable estimates of solvency capital by incorporating the frequency, severity, and variability of potential insurance losses. The findings may indicate that insurers with higher levels of risk exposure require stronger capital positions to maintain adequate solvency protection. The study may also reveal that stochastic and simulation-based approaches can provide more flexible estimates of solvency capital under different risk scenarios compared with approaches based solely on historical averages. The findings are expected to provide useful information to insurance companies, actuaries, regulators, investors, and other stakeholders. Insurance companies may use the findings to improve capital planning, risk assessment, solvency management, and financial decision-making. Actuaries may benefit from the application of quantitative risk models in estimating capital requirements that reflect the uncertainty surrounding future losses. Regulators may also use the findings to strengthen solvency assessment and ensure that insurers maintain sufficient capital to withstand adverse financial conditions. The study concludes that actuarial risk models provide an important basis for estimating insurance solvency capital because they enable insurers to quantify potential losses and align capital requirements with their underlying risk exposure. It is therefore recommended that insurance companies adopt appropriate actuarial models, regularly update their risk assumptions, conduct stress and sensitivity analyses, and maintain adequate solvency capital to protect policyholders and support long-term financial stability.

Keywords: Insurance solvency capital, actuarial risk models, capital requirements, available capital, required capital, solvency margin, capital adequacy, claims frequency, claims severity, aggregate claims, insurance liabilities, risk exposure, stochastic modelling, simulation, financial stability.